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Record W2794959216 · doi:10.1177/0164027518766422

Chronic Discrimination and Sleep Problems in Late Life: Religious Involvement as Buffer

2018· article· en· W2794959216 on OpenAlexaff
Alex Bierman, Yeonjung Lee, Scott Schieman

Bibliographic record

VenueResearch on Aging · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConfoundingAssociation (psychology)Sleep (system call)PsychologyChronic stressGerontologyMedicineClinical psychologyDemographyInternal medicine

Abstract

fetched live from OpenAlex

The association between chronic discrimination and sleep problems is important to examine in older adults because sleep is highly reactive to stress and impaired sleep has diverse adverse health effects. The association between chronic discrimination and sleep problems may, however, be confounded by a number of time-stable influences, and this association may also vary by religious involvement. In three waves (2006, 2010, and 2014) of the Health and Retirement Study ( N = 7,130), the overall association between chronic discrimination and sleep problems is negated in econometric models that control for all time-stable sources of confounding. Religious involvement does not modify this association for men, but a significant association is found among women who do not attend religious services. These analyses suggest that the association between chronic discrimination and sleep quality in late life is substantially inflated due to unobserved time-stable confounders, although women who do not attend religious services may be at risk.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.136
GPT teacher head0.466
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations63
Published2018
Admission routes1
Has abstractyes

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